Overview

Brought to you by YData

Dataset statistics

Number of variables16
Number of observations52413
Missing cells118109
Missing cells (%)14.1%
Duplicate rows1021
Duplicate rows (%)1.9%
Total size in memory8.8 MiB
Average record size in memory176.3 B

Variable types

Numeric16

Alerts

Dataset has 1021 (1.9%) duplicate rowsDuplicates
13169_FERM0101.Agitation_PV is highly overall correlated with 13169_FERM0101.Biocontainer_Pressure_PV and 5 other fieldsHigh correlation
13169_FERM0101.Air_Sparge_PV is highly overall correlated with 13169_FERM0101.DO_1_PV and 1 other fieldsHigh correlation
13169_FERM0101.Biocontainer_Pressure_PV is highly overall correlated with 13169_FERM0101.Agitation_PV and 4 other fieldsHigh correlation
13169_FERM0101.DO_1_PV is highly overall correlated with 13169_FERM0101.Agitation_PV and 7 other fieldsHigh correlation
13169_FERM0101.DO_2_PV is highly overall correlated with 13169_FERM0101.Biocontainer_Pressure_PV and 4 other fieldsHigh correlation
13169_FERM0101.Gas_Overlay_PV is highly overall correlated with 13169_FERM0101.Agitation_PV and 3 other fieldsHigh correlation
13169_FERM0101.Load_Cell_Net_PV is highly overall correlated with 13169_FERM0101.Agitation_PV and 6 other fieldsHigh correlation
13169_FERM0101.PUMP_1_TOTAL is highly overall correlated with 13169_FERM0101.PUMP_2_TOTALHigh correlation
13169_FERM0101.PUMP_2_PV is highly overall correlated with 13169_FERM0101.Agitation_PV and 6 other fieldsHigh correlation
13169_FERM0101.PUMP_2_TOTAL is highly overall correlated with 13169_FERM0101.Biocontainer_Pressure_PV and 4 other fieldsHigh correlation
13169_FERM0101.Single_Use_DO_PV is highly overall correlated with 13169_FERM0101.DO_1_PV and 4 other fieldsHigh correlation
13169_FERM0101.Single_Use_pH_PV is highly overall correlated with 13169_FERM0101.DO_1_PV and 2 other fieldsHigh correlation
13169_FERM0101.Temperatura_PV is highly overall correlated with 13169_FERM0101.DO_1_PV and 3 other fieldsHigh correlation
13169_FERM0101.pH_1_PV is highly overall correlated with 13169_FERM0101.Agitation_PV and 4 other fieldsHigh correlation
13169_FERM0101.pH_2_PV is highly overall correlated with 13169_FERM0101.DO_2_PVHigh correlation
13169_FERM0101.Agitation_PV has 4474 (8.5%) missing valuesMissing
13169_FERM0101.Air_Sparge_PV has 4474 (8.5%) missing valuesMissing
13169_FERM0101.Biocontainer_Pressure_PV has 4468 (8.5%) missing valuesMissing
13169_FERM0101.DO_1_PV has 4472 (8.5%) missing valuesMissing
13169_FERM0101.DO_2_PV has 51018 (97.3%) missing valuesMissing
13169_FERM0101.Gas_Overlay_PV has 4474 (8.5%) missing valuesMissing
13169_FERM0101.Load_Cell_Net_PV has 4471 (8.5%) missing valuesMissing
13169_FERM0101.pH_1_PV has 4473 (8.5%) missing valuesMissing
13169_FERM0101.pH_2_PV has 4473 (8.5%) missing valuesMissing
13169_FERM0101.PUMP_1_PV has 4474 (8.5%) missing valuesMissing
13169_FERM0101.PUMP_1_TOTAL has 4473 (8.5%) missing valuesMissing
13169_FERM0101.PUMP_2_PV has 4473 (8.5%) missing valuesMissing
13169_FERM0101.PUMP_2_TOTAL has 4473 (8.5%) missing valuesMissing
13169_FERM0101.Single_Use_DO_PV has 4472 (8.5%) missing valuesMissing
13169_FERM0101.Single_Use_pH_PV has 4474 (8.5%) missing valuesMissing
13169_FERM0101.Temperatura_PV has 4473 (8.5%) missing valuesMissing
13169_FERM0101.DO_1_PV is highly skewed (γ1 = 122.1420684)Skewed
13169_FERM0101.pH_1_PV is highly skewed (γ1 = 45.18544527)Skewed
13169_FERM0101.pH_2_PV is highly skewed (γ1 = 31.3612597)Skewed
13169_FERM0101.PUMP_1_PV is highly skewed (γ1 = 85.14922251)Skewed
13169_FERM0101.Agitation_PV has 28162 (53.7%) zerosZeros
13169_FERM0101.Air_Sparge_PV has 43732 (83.4%) zerosZeros
13169_FERM0101.DO_1_PV has 37638 (71.8%) zerosZeros
13169_FERM0101.DO_2_PV has 598 (1.1%) zerosZeros
13169_FERM0101.Gas_Overlay_PV has 21897 (41.8%) zerosZeros
13169_FERM0101.Load_Cell_Net_PV has 652 (1.2%) zerosZeros
13169_FERM0101.PUMP_1_PV has 47919 (91.4%) zerosZeros
13169_FERM0101.PUMP_1_TOTAL has 4356 (8.3%) zerosZeros
13169_FERM0101.PUMP_2_PV has 41258 (78.7%) zerosZeros
13169_FERM0101.PUMP_2_TOTAL has 12867 (24.5%) zerosZeros

Reproduction

Analysis started2024-09-29 18:17:04.530899
Analysis finished2024-09-29 18:17:24.502259
Duration19.97 seconds
Software versionydata-profiling v0.0.dev0
Download configurationconfig.json

Variables

13169_FERM0101.Agitation_PV
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct953
Distinct (%)2.0%
Missing4474
Missing (%)8.5%
Infinite0
Infinite (%)0.0%
Mean22.050232
Minimum0
Maximum80
Zeros28162
Zeros (%)53.7%
Negative0
Negative (%)0.0%
Memory size2.8 MiB
2024-09-29T20:17:24.546896image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q336
95-th percentile80
Maximum80
Range80
Interquartile range (IQR)36

Descriptive statistics

Standard deviation31.46826
Coefficient of variation (CV)1.427117
Kurtosis-0.53483127
Mean22.050232
Median Absolute Deviation (MAD)0
Skewness1.0724786
Sum1057066.1
Variance990.25142
MonotonicityNot monotonic
2024-09-29T20:17:24.622953image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 28162
53.7%
80 9426
 
18.0%
20 5626
 
10.7%
36 2769
 
5.3%
44 510
 
1.0%
40 439
 
0.8%
65.63200073 16
 
< 0.1%
32 15
 
< 0.1%
28 13
 
< 0.1%
65.6 5
 
< 0.1%
Other values (943) 958
 
1.8%
(Missing) 4474
 
8.5%
ValueCountFrequency (%)
0 28162
53.7%
6.616304524 1
 
< 0.1%
11.24572229 1
 
< 0.1%
14.62788387 1
 
< 0.1%
17.83681616 1
 
< 0.1%
19.94803772 1
 
< 0.1%
20 5626
 
10.7%
20.02604613 1
 
< 0.1%
20.02833033 1
 
< 0.1%
20.03770076 1
 
< 0.1%
ValueCountFrequency (%)
80 9426
18.0%
79.99999067 1
 
< 0.1%
79.99991745 1
 
< 0.1%
79.99984741 1
 
< 0.1%
79.99977417 1
 
< 0.1%
79.99970093 1
 
< 0.1%
79.99963047 1
 
< 0.1%
79.99955724 1
 
< 0.1%
79.9994873 1
 
< 0.1%
79.99941406 1
 
< 0.1%

13169_FERM0101.Air_Sparge_PV
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct4208
Distinct (%)8.8%
Missing4474
Missing (%)8.5%
Infinite0
Infinite (%)0.0%
Mean2.6015016
Minimum0
Maximum160.03796
Zeros43732
Zeros (%)83.4%
Negative0
Negative (%)0.0%
Memory size2.8 MiB
2024-09-29T20:17:24.695156image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile12.517292
Maximum160.03796
Range160.03796
Interquartile range (IQR)0

Descriptive statistics

Standard deviation11.546708
Coefficient of variation (CV)4.438478
Kurtosis22.415211
Mean2.6015016
Median Absolute Deviation (MAD)0
Skewness4.7464114
Sum124713.38
Variance133.32645
MonotonicityNot monotonic
2024-09-29T20:17:24.769408image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 43732
83.4%
24.75490008 1
 
< 0.1%
17.85708692 1
 
< 0.1%
16.21728604 1
 
< 0.1%
64.81973733 1
 
< 0.1%
63.97083238 1
 
< 0.1%
63.91876717 1
 
< 0.1%
8.726323951 1
 
< 0.1%
48.72169945 1
 
< 0.1%
64.17792565 1
 
< 0.1%
Other values (4198) 4198
 
8.0%
(Missing) 4474
 
8.5%
ValueCountFrequency (%)
0 43732
83.4%
0.0002475493859 1
 
< 0.1%
0.001360281915 1
 
< 0.1%
0.001989711373 1
 
< 0.1%
0.002135679508 1
 
< 0.1%
0.002647277473 1
 
< 0.1%
0.002974020814 1
 
< 0.1%
0.004107638302 1
 
< 0.1%
0.004297878198 1
 
< 0.1%
0.004515341351 1
 
< 0.1%
ValueCountFrequency (%)
160.0379551 1
< 0.1%
159.9992148 1
< 0.1%
159.9865597 1
< 0.1%
128.1523543 1
< 0.1%
65.25401611 1
< 0.1%
65.24246826 1
< 0.1%
65.21151193 1
< 0.1%
65.16242676 1
< 0.1%
65.13093367 1
< 0.1%
65.10684814 1
< 0.1%

13169_FERM0101.Biocontainer_Pressure_PV
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct24619
Distinct (%)51.3%
Missing4468
Missing (%)8.5%
Infinite0
Infinite (%)0.0%
Mean208.03724
Minimum-14.382141
Maximum480
Zeros0
Zeros (%)0.0%
Negative21283
Negative (%)40.6%
Memory size2.8 MiB
2024-09-29T20:17:24.844306image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/

Quantile statistics

Minimum-14.382141
5-th percentile-2.2424744
Q1-0.80440063
median0.84461253
Q3480
95-th percentile480
Maximum480
Range494.38214
Interquartile range (IQR)480.8044

Descriptive statistics

Standard deviation238.23881
Coefficient of variation (CV)1.1451738
Kurtosis-1.929464
Mean208.03724
Median Absolute Deviation (MAD)2.933963
Skewness0.26547128
Sum9974345.6
Variance56757.729
MonotonicityNot monotonic
2024-09-29T20:17:24.916931image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
480 20815
39.7%
-0.8044006348 134
 
0.3%
-0.7841430664 114
 
0.2%
-0.844909668 92
 
0.2%
-0.6018493652 77
 
0.1%
-1.898150635 68
 
0.1%
-0.7638916016 66
 
0.1%
-0.561340332 60
 
0.1%
-0.3790527344 58
 
0.1%
-1.938659668 51
 
0.1%
Other values (24609) 26410
50.4%
(Missing) 4468
 
8.5%
ValueCountFrequency (%)
-14.38214144 1
< 0.1%
-13.91018096 1
< 0.1%
-8.398524776 1
< 0.1%
-7.526334526 1
< 0.1%
-7.504755495 1
< 0.1%
-7.429657229 1
< 0.1%
-7.375883042 1
< 0.1%
-7.269022471 1
< 0.1%
-7.236778352 1
< 0.1%
-7.221018576 1
< 0.1%
ValueCountFrequency (%)
480 20815
39.7%
415.6497793 1
 
< 0.1%
374.626098 1
 
< 0.1%
185.1478871 1
 
< 0.1%
159.8366766 1
 
< 0.1%
119.3277616 1
 
< 0.1%
43.80006505 1
 
< 0.1%
14.9131958 1
 
< 0.1%
11.23726307 1
 
< 0.1%
10.81834783 1
 
< 0.1%

13169_FERM0101.DO_1_PV
Real number (ℝ)

HIGH CORRELATION  MISSING  SKEWED  ZEROS 

Distinct9118
Distinct (%)19.0%
Missing4472
Missing (%)8.5%
Infinite0
Infinite (%)0.0%
Mean5.6616598
Minimum0
Maximum4262.8
Zeros37638
Zeros (%)71.8%
Negative0
Negative (%)0.0%
Memory size2.8 MiB
2024-09-29T20:17:24.987561image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile26.313652
Maximum4262.8
Range4262.8
Interquartile range (IQR)0

Descriptive statistics

Standard deviation23.656879
Coefficient of variation (CV)4.1784353
Kurtosis21875.925
Mean5.6616598
Median Absolute Deviation (MAD)0
Skewness122.14207
Sum271425.63
Variance559.64794
MonotonicityNot monotonic
2024-09-29T20:17:25.057967image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 37638
71.8%
54.86001587 51
 
0.1%
55.01640625 32
 
0.1%
54.09481201 25
 
< 0.1%
55.32360229 23
 
< 0.1%
54.7092041 17
 
< 0.1%
57.62766113 17
 
< 0.1%
11.97207336 16
 
< 0.1%
54.25120239 14
 
< 0.1%
58.13261108 9
 
< 0.1%
Other values (9108) 10099
 
19.3%
(Missing) 4472
 
8.5%
ValueCountFrequency (%)
0 37638
71.8%
0.06301856686 1
 
< 0.1%
0.3278843446 1
 
< 0.1%
0.7292058518 1
 
< 0.1%
0.7303370476 3
 
< 0.1%
0.8807134628 4
 
< 0.1%
0.9272299767 2
 
< 0.1%
1.18729105 1
 
< 0.1%
1.191011238 1
 
< 0.1%
1.226674461 6
 
< 0.1%
ValueCountFrequency (%)
4262.8 1
< 0.1%
99.46989484 1
< 0.1%
97.62893541 1
< 0.1%
93.40368581 1
< 0.1%
89.05321205 1
< 0.1%
88.85593827 1
< 0.1%
87.50954433 1
< 0.1%
87.38304892 1
< 0.1%
87.31055529 1
< 0.1%
86.60829847 1
< 0.1%

13169_FERM0101.DO_2_PV
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct50
Distinct (%)3.6%
Missing51018
Missing (%)97.3%
Infinite0
Infinite (%)0.0%
Mean1.0710739
Minimum-0.0076965332
Maximum80.148999
Zeros598
Zeros (%)1.1%
Negative729
Negative (%)1.4%
Memory size2.8 MiB
2024-09-29T20:17:25.127009image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/

Quantile statistics

Minimum-0.0076965332
5-th percentile-0.0076965332
Q1-0.0076965332
median-0.0076965332
Q30
95-th percentile0
Maximum80.148999
Range80.156696
Interquartile range (IQR)0.0076965332

Descriptive statistics

Standard deviation5.6689464
Coefficient of variation (CV)5.2927689
Kurtosis81.317614
Mean1.0710739
Median Absolute Deviation (MAD)0
Skewness7.9019118
Sum1494.148
Variance32.136954
MonotonicityNot monotonic
2024-09-29T20:17:25.202926image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-0.007696533203 727
 
1.4%
0 598
 
1.1%
15.54459381 4
 
< 0.1%
15.85799103 4
 
< 0.1%
17.08918915 4
 
< 0.1%
16.00909271 4
 
< 0.1%
17.70478973 4
 
< 0.1%
16.47359009 2
 
< 0.1%
16.77579346 2
 
< 0.1%
18.16928864 2
 
< 0.1%
Other values (40) 44
 
0.1%
(Missing) 51018
97.3%
ValueCountFrequency (%)
-0.007696533203 727
1.4%
-0.00534002542 1
 
< 0.1%
-0.002366666671 1
 
< 0.1%
0 598
1.1%
13.38047325 1
 
< 0.1%
13.84329987 1
 
< 0.1%
14.30779877 1
 
< 0.1%
14.61559753 1
 
< 0.1%
15.19045087 1
 
< 0.1%
15.23679352 1
 
< 0.1%
ValueCountFrequency (%)
80.14899902 1
< 0.1%
75.35291748 1
< 0.1%
67.62434082 1
< 0.1%
59.89576416 1
< 0.1%
53.25288086 1
< 0.1%
46.44940451 1
< 0.1%
39.64812622 1
< 0.1%
32.53515015 1
< 0.1%
26.20007019 1
< 0.1%
26.04896851 1
< 0.1%

13169_FERM0101.Gas_Overlay_PV
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct26043
Distinct (%)54.3%
Missing4474
Missing (%)8.5%
Infinite0
Infinite (%)0.0%
Mean2.3886798
Minimum0
Maximum20.592549
Zeros21897
Zeros (%)41.8%
Negative0
Negative (%)0.0%
Memory size2.8 MiB
2024-09-29T20:17:25.277270image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median3.9995871
Q34.0000679
95-th percentile4.0008234
Maximum20.592549
Range20.592549
Interquartile range (IQR)4.0000679

Descriptive statistics

Standard deviation2.5246707
Coefficient of variation (CV)1.0569314
Kurtosis5.3445487
Mean2.3886798
Median Absolute Deviation (MAD)0.0022183658
Skewness1.3765313
Sum114510.92
Variance6.3739623
MonotonicityNot monotonic
2024-09-29T20:17:25.347488image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 21897
41.8%
7.999977035 1
 
< 0.1%
3.999616532 1
 
< 0.1%
4.000109859 1
 
< 0.1%
3.999795893 1
 
< 0.1%
3.999985455 1
 
< 0.1%
3.999625962 1
 
< 0.1%
4.000216767 1
 
< 0.1%
4.000467454 1
 
< 0.1%
4.000161089 1
 
< 0.1%
Other values (26033) 26033
49.7%
(Missing) 4474
 
8.5%
ValueCountFrequency (%)
0 21897
41.8%
2.176892399 1
 
< 0.1%
2.807917978 1
 
< 0.1%
3.612518024 1
 
< 0.1%
3.91659969 1
 
< 0.1%
3.917776644 1
 
< 0.1%
3.923629329 1
 
< 0.1%
3.924082301 1
 
< 0.1%
3.924942467 1
 
< 0.1%
3.927212341 1
 
< 0.1%
ValueCountFrequency (%)
20.5925486 1
< 0.1%
20.45979972 1
< 0.1%
20.31759869 1
< 0.1%
20.10388335 1
< 0.1%
20.047896 1
< 0.1%
19.98131058 1
< 0.1%
19.62791891 1
< 0.1%
19.55478174 1
< 0.1%
19.40977614 1
< 0.1%
19.3002427 1
< 0.1%

13169_FERM0101.Load_Cell_Net_PV
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct13986
Distinct (%)29.2%
Missing4471
Missing (%)8.5%
Infinite0
Infinite (%)0.0%
Mean664.33112
Minimum-24.8
Maximum1700.8265
Zeros652
Zeros (%)1.2%
Negative22957
Negative (%)43.8%
Memory size2.8 MiB
2024-09-29T20:17:25.415648image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/

Quantile statistics

Minimum-24.8
5-th percentile-20.8
Q1-18.4
median0.4
Q31590.4
95-th percentile1667.2
Maximum1700.8265
Range1725.6265
Interquartile range (IQR)1608.8

Descriptive statistics

Standard deviation786.57557
Coefficient of variation (CV)1.1840113
Kurtosis-1.8367664
Mean664.33112
Median Absolute Deviation (MAD)20.8
Skewness0.34369475
Sum31849363
Variance618701.13
MonotonicityNot monotonic
2024-09-29T20:17:25.488625image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-18.4 3141
 
6.0%
-18 2221
 
4.2%
-19.2 1980
 
3.8%
-18.8 1339
 
2.6%
-19.6 1184
 
2.3%
-17.6 1066
 
2.0%
-20.8 953
 
1.8%
-1.6 727
 
1.4%
0 652
 
1.2%
-1.2 642
 
1.2%
Other values (13976) 34037
64.9%
(Missing) 4471
 
8.5%
ValueCountFrequency (%)
-24.8 5
 
< 0.1%
-24.71761569 1
 
< 0.1%
-24.4 415
0.8%
-24.31926593 1
 
< 0.1%
-24.0816474 1
 
< 0.1%
-24 231
0.4%
-23.6 20
 
< 0.1%
-23.2 30
 
0.1%
-22.8 68
 
0.1%
-22.54363077 1
 
< 0.1%
ValueCountFrequency (%)
1700.826514 1
 
< 0.1%
1697.284851 1
 
< 0.1%
1694.8 3
< 0.1%
1694.707966 1
 
< 0.1%
1694.69504 1
 
< 0.1%
1694.690943 1
 
< 0.1%
1694.504122 1
 
< 0.1%
1694.488437 1
 
< 0.1%
1694.419704 1
 
< 0.1%
1694.408667 1
 
< 0.1%

13169_FERM0101.pH_1_PV
Real number (ℝ)

HIGH CORRELATION  MISSING  SKEWED 

Distinct7720
Distinct (%)16.1%
Missing4473
Missing (%)8.5%
Infinite0
Infinite (%)0.0%
Mean3.0936244
Minimum-0.03325119
Maximum318.32326
Zeros0
Zeros (%)0.0%
Negative10
Negative (%)< 0.1%
Memory size2.8 MiB
2024-09-29T20:17:25.561265image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/

Quantile statistics

Minimum-0.03325119
5-th percentile1.459322
Q11.5635605
median1.6657598
Q35.6397938
95-th percentile5.8827026
Maximum318.32326
Range318.35651
Interquartile range (IQR)4.0762333

Descriptive statistics

Standard deviation2.4418355
Coefficient of variation (CV)0.78931221
Kurtosis5791.9916
Mean3.0936244
Median Absolute Deviation (MAD)0.16427708
Skewness45.185445
Sum148308.35
Variance5.9625607
MonotonicityNot monotonic
2024-09-29T20:17:25.632892image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.66575985 2540
 
4.8%
1.589181519 1925
 
3.7%
1.627403831 1742
 
3.3%
1.501482773 1581
 
3.0%
1.690192032 1434
 
2.7%
1.563560486 1401
 
2.7%
1.624763489 1038
 
2.0%
1.603842735 812
 
1.5%
1.776680183 769
 
1.5%
1.550709343 764
 
1.5%
Other values (7710) 33934
64.7%
(Missing) 4473
 
8.5%
ValueCountFrequency (%)
-0.03325119019 9
 
< 0.1%
-0.02359831652 1
 
< 0.1%
0.4654800713 1
 
< 0.1%
1.372381592 169
 
0.3%
1.373102141 1
 
< 0.1%
1.373184669 1
 
< 0.1%
1.393197632 274
 
0.5%
1.394064886 1
 
< 0.1%
1.394091622 1
 
< 0.1%
1.433881187 723
1.4%
ValueCountFrequency (%)
318.3232613 1
< 0.1%
9.640264893 1
< 0.1%
9.607271576 2
< 0.1%
9.204669706 1
< 0.1%
8.355498317 1
< 0.1%
8.339646902 1
< 0.1%
8.134276743 1
< 0.1%
8.037700653 1
< 0.1%
7.96632477 1
< 0.1%
7.797498115 1
< 0.1%

13169_FERM0101.pH_2_PV
Real number (ℝ)

HIGH CORRELATION  MISSING  SKEWED 

Distinct118
Distinct (%)0.2%
Missing4473
Missing (%)8.5%
Infinite0
Infinite (%)0.0%
Mean-0.020121272
Minimum-0.3472353
Maximum5.3364357
Zeros0
Zeros (%)0.0%
Negative47930
Negative (%)91.4%
Memory size2.8 MiB
2024-09-29T20:17:25.701428image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/

Quantile statistics

Minimum-0.3472353
5-th percentile-0.011331558
Q1-0.011331558
median-0.011331558
Q3-0.011331558
95-th percentile-0.011331558
Maximum5.3364357
Range5.683671
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.088207911
Coefficient of variation (CV)-4.3838139
Kurtosis1866.2724
Mean-0.020121272
Median Absolute Deviation (MAD)0
Skewness31.36126
Sum-964.61378
Variance0.0077806356
MonotonicityNot monotonic
2024-09-29T20:17:25.767560image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-0.01133155823 46432
88.6%
-0.3472352982 1392
 
2.7%
-0.008146942851 1
 
< 0.1%
-0.002546493295 1
 
< 0.1%
-0.002445232963 1
 
< 0.1%
-0.002361036303 1
 
< 0.1%
-0.008968780803 1
 
< 0.1%
-0.008959279824 1
 
< 0.1%
-0.002393838423 1
 
< 0.1%
-0.005202465752 1
 
< 0.1%
Other values (108) 108
 
0.2%
(Missing) 4473
 
8.5%
ValueCountFrequency (%)
-0.3472352982 1392
 
2.7%
-0.2464711724 1
 
< 0.1%
-0.2437663103 1
 
< 0.1%
-0.01133155823 46432
88.6%
-0.01128516035 1
 
< 0.1%
-0.01125757921 1
 
< 0.1%
-0.01123713169 1
 
< 0.1%
-0.01119779867 1
 
< 0.1%
-0.01115897742 1
 
< 0.1%
-0.01113743357 1
 
< 0.1%
ValueCountFrequency (%)
5.336435699 1
< 0.1%
5.328588867 1
< 0.1%
5.313175201 1
< 0.1%
5.289915466 1
< 0.1%
5.220415497 1
< 0.1%
5.03152212 1
< 0.1%
4.328703015 1
< 0.1%
3.555673982 1
< 0.1%
3.310390472 1
< 0.1%
3.238727188 1
< 0.1%

13169_FERM0101.PUMP_1_PV
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct21
Distinct (%)< 0.1%
Missing4474
Missing (%)8.5%
Infinite0
Infinite (%)0.0%
Mean0.0095604034
Minimum0
Maximum80
Zeros47919
Zeros (%)91.4%
Negative0
Negative (%)0.0%
Memory size2.8 MiB
2024-09-29T20:17:25.828805image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum80
Range80
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.59196274
Coefficient of variation (CV)61.918176
Kurtosis8976.8438
Mean0.0095604034
Median Absolute Deviation (MAD)0
Skewness85.149223
Sum458.31618
Variance0.35041989
MonotonicityNot monotonic
2024-09-29T20:17:25.892172image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
0 47919
91.4%
9.604958678 1
 
< 0.1%
17.17764402 1
 
< 0.1%
14.017048 1
 
< 0.1%
16.93632362 1
 
< 0.1%
46.10962179 1
 
< 0.1%
15.17085849 1
 
< 0.1%
24.94687882 1
 
< 0.1%
13.71932577 1
 
< 0.1%
2.093653602 1
 
< 0.1%
Other values (11) 11
 
< 0.1%
(Missing) 4474
 
8.5%
ValueCountFrequency (%)
0 47919
91.4%
0.1744086634 1
 
< 0.1%
2.093653602 1
 
< 0.1%
6.226366375 1
 
< 0.1%
9.604958678 1
 
< 0.1%
9.861284704 1
 
< 0.1%
13.71932577 1
 
< 0.1%
14.017048 1
 
< 0.1%
15.17085849 1
 
< 0.1%
15.8142703 1
 
< 0.1%
ValueCountFrequency (%)
80 1
< 0.1%
46.10962179 1
< 0.1%
37.50559794 1
< 0.1%
37.35812266 1
< 0.1%
33.88020782 1
< 0.1%
27.91260746 1
< 0.1%
26.51290605 1
< 0.1%
24.94687882 1
< 0.1%
23.29409567 1
< 0.1%
17.17764402 1
< 0.1%

13169_FERM0101.PUMP_1_TOTAL
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct1927
Distinct (%)4.0%
Missing4473
Missing (%)8.5%
Infinite0
Infinite (%)0.0%
Mean79.654032
Minimum0
Maximum2987.5855
Zeros4356
Zeros (%)8.3%
Negative0
Negative (%)0.0%
Memory size2.8 MiB
2024-09-29T20:17:25.962245image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q112.4
median24.800002
Q374.399982
95-th percentile171.1201
Maximum2987.5855
Range2987.5855
Interquartile range (IQR)61.999982

Descriptive statistics

Standard deviation303.57782
Coefficient of variation (CV)3.8112047
Kurtosis82.831229
Mean79.654032
Median Absolute Deviation (MAD)14.880002
Skewness9.0208213
Sum3818614.3
Variance92159.492
MonotonicityNot monotonic
2024-09-29T20:17:26.035704image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
9.919999695 5449
 
10.4%
0 4356
 
8.3%
14.88000031 3724
 
7.1%
126.4800171 2777
 
5.3%
24.80000153 2615
 
5.0%
39.67999573 2554
 
4.9%
111.5999878 1894
 
3.6%
17.36000061 1781
 
3.4%
44.63999329 1617
 
3.1%
27.28000183 1611
 
3.1%
Other values (1917) 19562
37.3%
(Missing) 4473
 
8.5%
ValueCountFrequency (%)
0 4356
8.3%
0.01440595995 1
 
< 0.1%
0.01606404052 1
 
< 0.1%
0.02197659851 1
 
< 0.1%
0.02228737934 1
 
< 0.1%
0.02404167863 1
 
< 0.1%
0.02668780752 1
 
< 0.1%
0.02736773691 1
 
< 0.1%
0.02824584114 1
 
< 0.1%
0.03205580463 1
 
< 0.1%
ValueCountFrequency (%)
2987.585547 479
0.9%
2820.466423 1
 
< 0.1%
2656.748096 1
 
< 0.1%
2647.073145 1
 
< 0.1%
2643.313685 1
 
< 0.1%
2637.828786 1
 
< 0.1%
2628.796657 1
 
< 0.1%
2605.964147 1
 
< 0.1%
2602.029636 1
 
< 0.1%
2592.706904 1
 
< 0.1%

13169_FERM0101.PUMP_2_PV
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct6277
Distinct (%)13.1%
Missing4473
Missing (%)8.5%
Infinite0
Infinite (%)0.0%
Mean0.42247978
Minimum0
Maximum46.867441
Zeros41258
Zeros (%)78.7%
Negative0
Negative (%)0.0%
Memory size2.8 MiB
2024-09-29T20:17:26.107851image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile3.8456169
Maximum46.867441
Range46.867441
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.5230382
Coefficient of variation (CV)3.6049967
Kurtosis52.1284
Mean0.42247978
Median Absolute Deviation (MAD)0
Skewness5.0206412
Sum20253.68
Variance2.3196454
MonotonicityNot monotonic
2024-09-29T20:17:26.175928image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 41258
78.7%
8 387
 
0.7%
1.179298782 2
 
< 0.1%
5.007370377 2
 
< 0.1%
1.04678557 2
 
< 0.1%
0.4849973679 2
 
< 0.1%
0.06495509423 2
 
< 0.1%
0.4498001785 2
 
< 0.1%
0.3825416718 2
 
< 0.1%
3.969618909 2
 
< 0.1%
Other values (6267) 6279
 
12.0%
(Missing) 4473
 
8.5%
ValueCountFrequency (%)
0 41258
78.7%
0.0001851918668 1
 
< 0.1%
0.0002571694422 1
 
< 0.1%
0.0003686000137 1
 
< 0.1%
0.0004702092422 1
 
< 0.1%
0.0005623292117 1
 
< 0.1%
0.000570922575 1
 
< 0.1%
0.0007132517626 1
 
< 0.1%
0.0008206312514 1
 
< 0.1%
0.001044578116 1
 
< 0.1%
ValueCountFrequency (%)
46.86744091 1
 
< 0.1%
45.76459981 1
 
< 0.1%
28.69340853 1
 
< 0.1%
27.79323548 1
 
< 0.1%
14.11384463 1
 
< 0.1%
9.292723103 1
 
< 0.1%
8 387
0.7%
7.999051264 1
 
< 0.1%
7.998912505 1
 
< 0.1%
7.998295849 1
 
< 0.1%

13169_FERM0101.PUMP_2_TOTAL
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct8846
Distinct (%)18.5%
Missing4473
Missing (%)8.5%
Infinite0
Infinite (%)0.0%
Mean3636.4287
Minimum0
Maximum22260.513
Zeros12867
Zeros (%)24.5%
Negative0
Negative (%)0.0%
Memory size2.8 MiB
2024-09-29T20:17:26.245037image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1713.5152
Q37517.3813
95-th percentile8539.3891
Maximum22260.513
Range22260.513
Interquartile range (IQR)7517.3813

Descriptive statistics

Standard deviation3541.1536
Coefficient of variation (CV)0.97379981
Kurtosis-1.4544009
Mean3636.4287
Median Absolute Deviation (MAD)1713.5152
Skewness0.30508701
Sum1.7433039 × 108
Variance12539769
MonotonicityNot monotonic
2024-09-29T20:17:26.784556image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 12867
24.5%
8539.389063 2741
 
5.2%
7637.635938 2075
 
4.0%
7121.058594 1851
 
3.5%
1583.483008 1686
 
3.2%
6378.242188 1516
 
2.9%
7744.296875 1221
 
2.3%
1486.330176 1204
 
2.3%
19.79999695 1186
 
2.3%
8691.0625 1062
 
2.0%
Other values (8836) 20531
39.2%
(Missing) 4473
 
8.5%
ValueCountFrequency (%)
0 12867
24.5%
0.03293879197 1
 
< 0.1%
0.03615813777 1
 
< 0.1%
0.0439114691 1
 
< 0.1%
0.1094205179 1
 
< 0.1%
0.1271441127 1
 
< 0.1%
0.1373701266 1
 
< 0.1%
0.1898651619 1
 
< 0.1%
0.4262756849 1
 
< 0.1%
0.4288547956 1
 
< 0.1%
ValueCountFrequency (%)
22260.5125 1
< 0.1%
22105.09613 1
< 0.1%
21906.81499 1
< 0.1%
21708.53363 1
< 0.1%
21510.25238 1
< 0.1%
21311.5077 1
< 0.1%
21113.68988 1
< 0.1%
20915.28438 1
< 0.1%
20716.66627 1
< 0.1%
20518.72188 1
< 0.1%

13169_FERM0101.Single_Use_DO_PV
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct10686
Distinct (%)22.3%
Missing4472
Missing (%)8.5%
Infinite0
Infinite (%)0.0%
Mean587.29992
Minimum0
Maximum806.5248
Zeros27
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size2.8 MiB
2024-09-29T20:17:26.852006image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile12.513127
Q1655.08677
median700.94805
Q3799.99199
95-th percentile799.99199
Maximum806.5248
Range806.5248
Interquartile range (IQR)144.90522

Descriptive statistics

Standard deviation296.336
Coefficient of variation (CV)0.50457354
Kurtosis-0.1524629
Mean587.29992
Median Absolute Deviation (MAD)99.043945
Skewness-1.2872274
Sum28155745
Variance87815.024
MonotonicityNot monotonic
2024-09-29T20:17:26.930525image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
799.9919922 16984
32.4%
699.8442871 2726
 
5.2%
693.1138184 1985
 
3.8%
700.9480469 1982
 
3.8%
656.0895996 1841
 
3.5%
655.0867676 1433
 
2.7%
655.8924316 1319
 
2.5%
658.3754395 1053
 
2.0%
659.2979004 858
 
1.6%
730.7864746 787
 
1.5%
Other values (10676) 16973
32.4%
(Missing) 4472
 
8.5%
ValueCountFrequency (%)
0 27
0.1%
1.104355875 1
 
< 0.1%
1.109617987 1
 
< 0.1%
1.128502442 1
 
< 0.1%
1.151514591 1
 
< 0.1%
1.158029039 1
 
< 0.1%
1.161866093 1
 
< 0.1%
1.165701604 1
 
< 0.1%
1.183359297 1
 
< 0.1%
1.324367579 1
 
< 0.1%
ValueCountFrequency (%)
806.5248047 377
 
0.7%
804.9375485 1
 
< 0.1%
804.7007632 1
 
< 0.1%
802.7157946 1
 
< 0.1%
801.9368407 1
 
< 0.1%
799.9919922 16984
32.4%
799.977278 1
 
< 0.1%
799.9266658 1
 
< 0.1%
799.830605 1
 
< 0.1%
799.7720565 1
 
< 0.1%

13169_FERM0101.Single_Use_pH_PV
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct1714
Distinct (%)3.6%
Missing4474
Missing (%)8.5%
Infinite0
Infinite (%)0.0%
Mean589.88329
Minimum-788.248
Maximum800.11997
Zeros0
Zeros (%)0.0%
Negative152
Negative (%)0.3%
Memory size2.8 MiB
2024-09-29T20:17:27.003250image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/

Quantile statistics

Minimum-788.248
5-th percentile5.7600098
Q16.0879883
median799.848
Q3799.91201
95-th percentile800.01602
Maximum800.11997
Range1588.368
Interquartile range (IQR)793.82402

Descriptive statistics

Standard deviation351.09812
Coefficient of variation (CV)0.5951993
Kurtosis-0.76740168
Mean589.88329
Median Absolute Deviation (MAD)0.10400391
Skewness-1.0860302
Sum28278415
Variance123269.89
MonotonicityNot monotonic
2024-09-29T20:17:27.077769image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
799.8640137 5484
 
10.5%
799.9120117 5249
 
10.0%
799.9679688 4307
 
8.2%
799.8399902 2391
 
4.6%
799.847998 2286
 
4.4%
799.7679688 2107
 
4.0%
6.087988281 1689
 
3.2%
799.6239746 1563
 
3.0%
799.8239746 1159
 
2.2%
5.760009766 1146
 
2.2%
Other values (1704) 20558
39.2%
(Missing) 4474
 
8.5%
ValueCountFrequency (%)
-788.247998 3
< 0.1%
-787.9280273 6
< 0.1%
-787.9200195 7
< 0.1%
-787.9120117 5
< 0.1%
-787.8560059 1
 
< 0.1%
-787.6720231 1
 
< 0.1%
-787.5999192 1
 
< 0.1%
-458.4514524 1
 
< 0.1%
-429.6835017 1
 
< 0.1%
-5.382378252 1
 
< 0.1%
ValueCountFrequency (%)
800.1199707 763
 
1.5%
800.0640137 457
 
0.9%
800.0319824 1079
 
2.1%
800.0160156 931
 
1.8%
799.9919922 1097
 
2.1%
799.9759766 727
 
1.4%
799.9679688 4307
8.2%
799.9279785 269
 
0.5%
799.9199707 633
 
1.2%
799.9120117 5249
10.0%

13169_FERM0101.Temperatura_PV
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct31515
Distinct (%)65.7%
Missing4473
Missing (%)8.5%
Infinite0
Infinite (%)0.0%
Mean17.538095
Minimum0.13422075
Maximum80.831995
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.8 MiB
2024-09-29T20:17:27.154732image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/

Quantile statistics

Minimum0.13422075
5-th percentile3.2079547
Q114.279996
median16.174336
Q323.367996
95-th percentile29.624002
Maximum80.831995
Range80.697774
Interquartile range (IQR)9.0880005

Descriptive statistics

Standard deviation8.0134996
Coefficient of variation (CV)0.45691963
Kurtosis-0.59374754
Mean17.538095
Median Absolute Deviation (MAD)3.9823411
Skewness0.030624877
Sum840776.25
Variance64.216176
MonotonicityNot monotonic
2024-09-29T20:17:27.231005image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
29.60000305 743
 
1.4%
29.60799866 711
 
1.4%
29.62400208 584
 
1.1%
29.57600403 578
 
1.1%
29.56000061 425
 
0.8%
29.64000549 339
 
0.6%
29.552005 259
 
0.5%
23.20000305 234
 
0.4%
3.207997894 232
 
0.4%
29.6559967 221
 
0.4%
Other values (31505) 43614
83.2%
(Missing) 4473
 
8.5%
ValueCountFrequency (%)
0.1342207533 1
 
< 0.1%
2.960000038 1
 
< 0.1%
2.983999062 1
 
< 0.1%
2.988781143 1
 
< 0.1%
2.99337338 1
 
< 0.1%
3.002415713 1
 
< 0.1%
3.007523384 1
 
< 0.1%
3.00849095 1
 
< 0.1%
3.015999794 10
< 0.1%
3.016047365 1
 
< 0.1%
ValueCountFrequency (%)
80.83199463 1
< 0.1%
31.59199524 1
< 0.1%
31.47200012 1
< 0.1%
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2024-09-29T20:17:11.785354image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-09-29T20:17:13.124870image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-09-29T20:17:14.223937image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-09-29T20:17:15.306619image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-09-29T20:17:16.410747image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-09-29T20:17:17.807984image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-09-29T20:17:18.870981image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-09-29T20:17:19.938415image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-09-29T20:17:21.048074image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-09-29T20:17:22.564246image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-09-29T20:17:23.756036image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-09-29T20:17:06.192619image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-09-29T20:17:07.481826image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-09-29T20:17:08.572118image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-09-29T20:17:09.639142image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-09-29T20:17:10.811816image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-09-29T20:17:11.847402image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-09-29T20:17:13.191787image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-09-29T20:17:14.289446image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-09-29T20:17:15.369316image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-09-29T20:17:16.475494image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-09-29T20:17:17.872155image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-09-29T20:17:18.934691image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-09-29T20:17:19.999150image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-09-29T20:17:21.116655image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-09-29T20:17:22.631382image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-09-29T20:17:23.829897image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-09-29T20:17:06.273992image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-09-29T20:17:07.556747image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-09-29T20:17:08.642657image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-09-29T20:17:09.903587image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-09-29T20:17:10.873538image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-09-29T20:17:11.917890image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-09-29T20:17:13.264132image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-09-29T20:17:14.358996image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-09-29T20:17:15.439489image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-09-29T20:17:16.851896image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-09-29T20:17:17.945728image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-09-29T20:17:19.004190image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-09-29T20:17:20.069736image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-09-29T20:17:21.188387image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-09-29T20:17:22.705936image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-09-29T20:17:23.904193image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-09-29T20:17:06.350277image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-09-29T20:17:07.630514image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-09-29T20:17:08.717402image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-09-29T20:17:09.974418image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-09-29T20:17:10.935037image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-09-29T20:17:11.986995image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-09-29T20:17:13.338272image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-09-29T20:17:14.430565image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-09-29T20:17:15.509269image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-09-29T20:17:16.925577image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-09-29T20:17:18.017949image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-09-29T20:17:19.075174image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-09-29T20:17:20.141176image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-09-29T20:17:21.269071image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-09-29T20:17:22.778682image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/

Correlations

2024-09-29T20:17:27.291306image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
13169_FERM0101.Agitation_PV13169_FERM0101.Air_Sparge_PV13169_FERM0101.Biocontainer_Pressure_PV13169_FERM0101.DO_1_PV13169_FERM0101.DO_2_PV13169_FERM0101.Gas_Overlay_PV13169_FERM0101.Load_Cell_Net_PV13169_FERM0101.PUMP_1_PV13169_FERM0101.PUMP_1_TOTAL13169_FERM0101.PUMP_2_PV13169_FERM0101.PUMP_2_TOTAL13169_FERM0101.Single_Use_DO_PV13169_FERM0101.Single_Use_pH_PV13169_FERM0101.Temperatura_PV13169_FERM0101.pH_1_PV13169_FERM0101.pH_2_PV
13169_FERM0101.Agitation_PV1.0000.444-0.5590.705-0.1660.6420.8610.012-0.2190.591-0.465-0.315-0.4680.4070.708-0.017
13169_FERM0101.Air_Sparge_PV0.4441.000-0.0780.5210.2470.2650.4040.0090.0190.5840.010-0.420-0.3640.4000.4130.044
13169_FERM0101.Biocontainer_Pressure_PV-0.559-0.0781.000-0.2070.672-0.768-0.713-0.0050.380-0.1580.612-0.2600.0370.096-0.2810.128
13169_FERM0101.DO_1_PV0.7050.521-0.2071.0000.2810.3980.6750.013-0.0530.699-0.129-0.637-0.6210.6420.6910.086
13169_FERM0101.DO_2_PV-0.1660.2470.6720.2811.000-0.304-0.102NaN0.4950.3750.767-0.698-0.4550.660-0.2210.790
13169_FERM0101.Gas_Overlay_PV0.6420.265-0.7680.398-0.3041.0000.7530.010-0.3000.337-0.527-0.006-0.2080.1750.419-0.088
13169_FERM0101.Load_Cell_Net_PV0.8610.404-0.7130.675-0.1020.7531.0000.013-0.2850.533-0.527-0.193-0.3470.3390.592-0.034
13169_FERM0101.PUMP_1_PV0.0120.009-0.0050.013NaN0.0100.0131.000-0.0050.009-0.004-0.009-0.0110.0160.0080.003
13169_FERM0101.PUMP_1_TOTAL-0.2190.0190.380-0.0530.495-0.300-0.285-0.0051.0000.0460.695-0.3210.1240.0610.0060.101
13169_FERM0101.PUMP_2_PV0.5910.584-0.1580.6990.3750.3370.5330.0090.0461.000-0.002-0.542-0.4940.5250.5100.052
13169_FERM0101.PUMP_2_TOTAL-0.4650.0100.612-0.1290.767-0.527-0.527-0.0040.695-0.0021.000-0.2810.0970.115-0.1440.146
13169_FERM0101.Single_Use_DO_PV-0.315-0.420-0.260-0.637-0.698-0.006-0.193-0.009-0.321-0.542-0.2811.0000.514-0.618-0.493-0.137
13169_FERM0101.Single_Use_pH_PV-0.468-0.3640.037-0.621-0.455-0.208-0.347-0.0110.124-0.4940.0970.5141.000-0.441-0.504-0.112
13169_FERM0101.Temperatura_PV0.4070.4000.0960.6420.6600.1750.3390.0160.0610.5250.115-0.618-0.4411.0000.4980.132
13169_FERM0101.pH_1_PV0.7080.413-0.2810.691-0.2210.4190.5920.0080.0060.510-0.144-0.493-0.5040.4981.000-0.039
13169_FERM0101.pH_2_PV-0.0170.0440.1280.0860.790-0.088-0.0340.0030.1010.0520.146-0.137-0.1120.132-0.0391.000

Missing values

2024-09-29T20:17:23.987556image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
A simple visualization of nullity by column.
2024-09-29T20:17:24.138219image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2024-09-29T20:17:24.335729image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

13169_FERM0101.Agitation_PV13169_FERM0101.Air_Sparge_PV13169_FERM0101.Biocontainer_Pressure_PV13169_FERM0101.DO_1_PV13169_FERM0101.DO_2_PV13169_FERM0101.Gas_Overlay_PV13169_FERM0101.Load_Cell_Net_PV13169_FERM0101.pH_1_PV13169_FERM0101.pH_2_PV13169_FERM0101.PUMP_1_PV13169_FERM0101.PUMP_1_TOTAL13169_FERM0101.PUMP_2_PV13169_FERM0101.PUMP_2_TOTAL13169_FERM0101.Single_Use_DO_PV13169_FERM0101.Single_Use_pH_PV13169_FERM0101.Temperatura_PV
DateTime
2023-03-15 00:00:00.0000.00.0480.00.0NaN0.0-20.0000001.56356-0.0113320.027.2800020.01486.330176655.892432799.62397518.163524
2023-03-15 00:15:00.0000.00.0480.00.0NaN0.0-17.3353881.56356-0.0113320.027.2800020.01486.330176655.892432799.62397518.102256
2023-03-15 00:30:00.0000.00.0480.00.0NaN0.0-20.0359171.56356-0.0113320.027.2800020.01486.330176655.892432799.62397518.070250
2023-03-15 00:45:00.0000.00.0480.00.0NaN0.0-20.2604541.56356-0.0113320.027.2800020.01486.330176655.892432799.62397518.004430
2023-03-15 01:00:00.0000.00.0480.00.0NaN0.0-20.3991361.56356-0.0113320.027.2800020.01486.330176655.892432799.62397518.020433
2023-03-15 01:15:00.0000.00.0480.00.0NaN0.0-20.4000001.56356-0.0113320.027.2800020.01480.795851655.892432799.62397517.924498
2023-03-15 01:30:00.0000.00.0480.00.0NaN0.0-17.8290691.56356-0.0113320.027.2800020.0361.983921655.892432799.62397517.928987
2023-03-15 01:45:00.0000.00.0480.00.0NaN0.0-20.4000001.56356-0.0113320.022.3400420.01486.330176655.892432799.62397517.940428
2023-03-15 02:00:00.0000.00.0480.00.0NaN0.0-20.4000001.56356-0.0113320.027.2800020.01486.330176655.892432799.62397517.847360
2023-03-15 02:15:00.0000.00.0480.00.0NaN0.0-20.4000001.56356-0.0113320.027.2800020.01486.330176655.892432799.62397517.715718
13169_FERM0101.Agitation_PV13169_FERM0101.Air_Sparge_PV13169_FERM0101.Biocontainer_Pressure_PV13169_FERM0101.DO_1_PV13169_FERM0101.DO_2_PV13169_FERM0101.Gas_Overlay_PV13169_FERM0101.Load_Cell_Net_PV13169_FERM0101.pH_1_PV13169_FERM0101.pH_2_PV13169_FERM0101.PUMP_1_PV13169_FERM0101.PUMP_1_TOTAL13169_FERM0101.PUMP_2_PV13169_FERM0101.PUMP_2_TOTAL13169_FERM0101.Single_Use_DO_PV13169_FERM0101.Single_Use_pH_PV13169_FERM0101.Temperatura_PV
DateTime
2024-09-10 21:45:00.00080.024.7549000.1250000.013.3804734.0009681659.65.874312-0.3472350.029.7600017.1717861153.60570914.9940765.80000029.560001
2024-09-10 22:00:00.00080.00.000000-0.1884230.017.7047903.9997671659.65.882534-0.3472350.029.7600010.0000001185.60771518.5827355.80000029.640005
2024-09-10 22:15:00.00080.00.000000-0.1594800.020.6428803.9998751659.65.882534-0.3472350.029.7600010.0000001215.84169922.3271725.80000029.600003
2024-09-10 22:30:00.00080.00.000000-0.1645040.017.4164573.9999521659.65.882534-0.3472350.029.7600010.0000001244.14433618.0431665.80237329.607999
2024-09-10 22:45:00.00080.00.000000-0.1824740.020.3294833.9998941660.05.874312-0.3472350.029.7600012.6074111267.12666021.7553975.80564129.552005
2024-09-10 23:00:00.00080.00.000000-0.1587970.017.6169313.9998791659.65.874398-0.3472350.08.6700842.9349001298.23300818.6449915.80000029.640005
2024-09-10 23:15:00.00080.02.827101-0.1967590.014.6155984.0004391660.05.874312-0.3472350.029.7600014.8133931326.56709015.3381305.80000029.600003
2024-09-10 23:30:00.00080.00.000000-0.1889620.026.2000703.9998661660.05.874312-0.3472350.029.7600016.8855861367.73721527.6330935.80553929.600003
2024-09-10 23:45:00.00080.00.000000-0.1340660.021.7229784.0002711659.65.882534-0.3472350.029.7600010.0000001405.27568423.3956855.80000029.607999
2024-09-11 00:00:00.00080.00.000000-0.3993040.016.2292343.9998851660.05.874518-0.3472350.029.7600017.1821581432.26459516.6259005.80000029.605613

Duplicate rows

Most frequently occurring

13169_FERM0101.Agitation_PV13169_FERM0101.Air_Sparge_PV13169_FERM0101.Biocontainer_Pressure_PV13169_FERM0101.DO_1_PV13169_FERM0101.DO_2_PV13169_FERM0101.Gas_Overlay_PV13169_FERM0101.Load_Cell_Net_PV13169_FERM0101.pH_1_PV13169_FERM0101.pH_2_PV13169_FERM0101.PUMP_1_PV13169_FERM0101.PUMP_1_TOTAL13169_FERM0101.PUMP_2_PV13169_FERM0101.PUMP_2_TOTAL13169_FERM0101.Single_Use_DO_PV13169_FERM0101.Single_Use_pH_PV13169_FERM0101.Temperatura_PV# duplicates
1020NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN4467
4070.00.0480.00.0NaN0.0-19.21.66576-0.0113320.0126.4800170.08539.389063699.844287799.91201225.94399712
6040.00.0480.00.0NaN0.0-18.41.66576-0.0113320.0126.4800170.08539.389063699.844287799.91201214.44000512
4090.00.0480.00.0NaN0.0-19.21.66576-0.0113320.0126.4800170.08539.389063699.844287799.91201225.98400010
4930.00.0480.00.0NaN0.0-18.81.66576-0.0113320.0126.4800170.08539.389063699.844287799.91201224.59199510
5110.00.0480.00.0NaN0.0-18.81.66576-0.0113320.0126.4800170.08539.389063699.844287799.91201224.92800610
7490.00.0480.00.0NaN0.0-18.01.66576-0.0113320.0126.4800170.08539.389063699.844287799.91201223.76799610
3200.00.0480.00.0NaN0.0-19.61.66576-0.0113320.0126.4800170.08539.389063699.844287799.91201225.4000039
4250.00.0480.00.0NaN0.0-19.21.66576-0.0113320.0126.4800170.08539.389063699.844287799.91201226.8160069
5990.00.0480.00.0NaN0.0-18.41.66576-0.0113320.0126.4800170.08539.389063699.844287799.91201214.3600019